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What students really think: unpacking AI ethics in educational assessments through a triadic framework

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Pubblicato in:International Journal of Educational Technology in Higher Education vol. 22, no. 1 (Dec 2025), p. 56
Autore principale: Lim, Tristan
Altri autori: Gottipati, Swapna, Cheong, Michelle
Pubblicazione:
Springer Nature B.V.
Soggetti:
Students
Assessments
Educational evaluation
Ontology
Systems design
Automation
Privacy
Cognitive ability
Ethics
Research & development > R&D
Feedback
Cognition & reasoning
Accountability
Artificial intelligence
Educational objectives
Education
Instructional scaffolding
Personalized learning
Literature reviews
Surveillance
Perceptions
Efficiency
Fairness
Risk assessment
Teaching
Ethical dilemmas
Morality
Frame analysis
Evaluation
Learning
Management
Effectiveness
Structural equation modeling
Learning Analytics
Dropout Rate
Intelligent Tutoring Systems
Influence of Technology
Diagnostic Tests
Learning Theories
Educational Technology
Grading
Student Experience
Network Analysis
Integrity
Interpersonal Relationship
At Risk Students
Instructional Effectiveness
Adaptive Testing
Educational Assessment
Formative Evaluation
Outcomes of Education
Language Processing
Data Processing
Algorithms
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